Hello 👋

About the materials

It is not enough to cover all important topics.

It is enough to teach you how to find answers and implement them yourself.

The datasets: Sheep Astragali

Sheep astragulus morphology from Iron Age Eastern Mediterranean.

nmar79. (2023). nmar79/Med_Sheep_Astragals: v0.1 (v0.1). Zenodo. https://doi.org/10.5281/zenodo.10276147

The datasets: Kiwulan Burials

Burial data from northeastern Taiwan ranging from the Iron Age through the European colonization period.

Li-Ying Wang & Ben Marwick, (2021). Compendium of R code and data for “A Bayesian networks approach to infer social changes from burials in northeastern Taiwan during the European colonization period”. Accessed 23 Aug 2021. Online at https://osf.io/xga6n/

Assignment 1: Case study

Assignment 1 consists of finding, importing, cleaning, and exploring/analysing a dataset.

1.1 Find, import, clean

Find a dataset that you want to work with, then use a script to download and clean the data.

If you can’t find a dataset, you can use the full, unmodified version of the workshop data here: https://osf.io/zem9p

1.2 Exploratory data analysis

If the EDA module is included in the workshop, then assignment 1 is extended to include EDA. Plot the distribution of at least two types of variables that you are interested in exploring further.

Create at least one plot with the relationship between two variables, and a summary table with the mean and standard deviation within groupings of a variable.

1.3 Data modelling

If the data modelling module is taught in the workshop, select at least two statistical models to apply to the data.

1.4 Communicating results

Use Quarto to communicate the results from the previous sections of assignment 1. This can be in the form of a report, short manuscript, presentation, or whatever format in Quarto you prefer.